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Hydrogen peroxide is commonly used as a sterilizing agent for medical devices and its use has recently been extended to N95 masks during PPE shortages as a result of the COVID-19 pandemic. The hydrogen peroxide remaining on the masks after sterilization could potentially pose a health hazard to the mask users. In the present study a colorimetric method was optimized for the determination of hydrogen peroxide on N95 masks following chemical sanitizations. The developed analytical method demonstrated an overall recovery of 98% ± 7%. The limit of detection ranged from 0.16 to 0.25 mg/mask, depending on the type of mask. The expanded measurement uncertainty was 13% (at a 95% confidence interval). The sanitization process itself introduced a significant variation in hydrogen peroxide load between masks. The ozone used in the sanitization process had no significant impact on analytical performance. Stamped and printed marks on the mask surfaces could induce biased readings. Hydrogen peroxide decomposes quickly on the mask surfaces so timing of analysis is an important factor in method standardization.•The validation data demonstrated that the in-house method is reliable and fit for the intended purpose, offering a sensitive, simple, rapid, and inexpensive method of residue monitoring.Traditional forestry, ecology, and fuels monitoring methods can be costly and error-prone, and are often used beyond their original assumptions due to difficulty or unavailability of more appropriate methods. These traditional methods tend to be rigid and may not be useful for detecting new ecological changes or required data at modern levels of precision [1]. The integration of Terrestrial Laser Scanning (TLS) methods into forest monitoring strategies can cost effectively standardize data collection, improve efficiency, and reduce error, with datasets that can easily be analyzed to better inform management decisions. Affordable (sub-$20K) off-the-shelf TLS units-such as the Leica BLK360- have been used commercially in the built environment but have untapped potential in the natural world for monitoring. Here, we provide a methodology that successfully integrates LiDAR scanning with existing monitoring methods. This new method•Allows for simplified and quick extraction of forestry, fuels and ecological vegetation variables from a single TLS point cloud and quick transect sampling.•Streamlines the data collection process, removes sampling bias, and produces data that can be easily processed to provide inputs for models and decision support frameworks.•Is adaptable to integrate additional or new environmental measurements.Sea level rise and coastal floods are disrupting coastal communities across the world. The impacts of coastal floods are magnified by the disruption of critical urban systems such as transportation. The flood-related closure of low-lying coastal roads and highways can increase travel time delays and accident risk. However, quantifying the flood-related disruption of the urban traffic system presents challenges. AZD7648 mouse Traffic systems are complex and highly dynamic, where congestion resulting from road closures may propagate rapidly from one area to another. Prior studies identify flood-related road closures by spatially overlaying coastal flood maps onto road network models, but simplifications within the representation of the road network with respect to the coastline or creeks may lead to an incorrect identification of flooded roads. We identify three corrections to reduce potential biases in the identification of flooded roads 1. We correct for the geometry of highways; 2. We correct for the elevation of bridges and highway overpasses; and 3. We identify and account for road-creek crossings. Accounting for these three corrections, we develop a methodology for accurately identifying flooded roads, improving our ability to quantify flood impacts on urban traffic systems and accident rates.Previously published methods for the analysis of metaldehyde were adapted for its reliable quantification in soil extracts. Varied methanol-water extraction solvents were trialed, but the use of pure methanol proved to be the most reliable approach for the scaled down methodology. Analysis of metaldehyde was done using LC-MS. Initially the method had problems with matrix suppression of the signal. The method was therefore further developed to overcome this challenge to avoid the costs and time demands of laborious clean-up protocols. This modification to the method involved use of the BEH Phenyl column instead of the C18 column initially used, and optimization of the gradient flow of the mobile phase. The optimized LC-MS method was validated and used for further research applications. In brief,•We investigated the recovery of metaldehyde from spiked soil samples.•The optimized LC-MS method achieved acceptable metaldehyde recoveries (100-132%, 109% on average) for a range of soil types.•The optimized method was suitable for high through-put analyzes.High-quality RNA is required for accurate gene expression and transcriptome analysis. The current methods of RNA extraction from berry fruits are either time-consuming or expensive. To simplify the conventional phenol-chloroform based RNA extraction method, we modified the protocol with less steps as well as the removal of the use of phenol. In this protocol, the extraction buffer is composed of hexadecyltrimethyl ammonium bromide (CTAB), polyvinylpyrrolidone (PVP), and Dithiothreitol (DTT). The method facilitates efficient removal of polysaccharides and phenolic compounds from both fruit pulp and fruit peel. Additionally, the protocol is phenol-free and less toxic than traditional phenol-containing method. High-quality RNA, with RNA Integrity Number value > 8, isolated by this method is applicable for RNA sequencing and qPCR. Only 3-4 working hours are required for one batch of RNA isolation.•Our method replaces the use of phenol-chloroform with chloroform, making the extraction less toxic.•The bilberry friut RNA is of high-quality and purity with less time input.Histological processing of mineralised tissue (e.g. bone) allows examining the anatomy of cells and tissues as well as the material properties of the tissue. However, resin-embedding offers limited control over the specimen position for cutting. Moreover, specific anatomical planes (coronal, sagittal) or defined landmarks are often missed with standard microtome sectioning. Here we describe a method to precisely locate a specific anatomical 2D plane or any anatomical feature of interest (e.g. bone lesions, newly formed bone, etc.) using 3D micro computed tomography (microCT), and to expose it using controlled-angle microtome cutting. The resulting sections and corresponding specimen's block surface offer correlative information of the same anatomical location, which can then be analysed using multiscale imaging. Moreover, this method can be combined with immunohistochemistry (IHC) to further identify any component of the bone microenvironment (cells, extracellular matrix, proteins, etc.) and guide subsequent in-depth analysis. Overall, this method allows to•Cut your specimens in a consistent position and precise manner using microCT-based controlled-angle microtome sectioning.•Locate and expose a specific anatomical plane (coronal, sagittal plane) or any other anatomical landmarks of interest based on microCT.•Identify any cell or tissue markers based on IHC to guide further in-depth examination of those regions of interest.Heat shock factor 1, HSF1, is one of several family members that recognize repeated nGAAn sequences associated with the heat shock element of heat shock and other genes. This transactivator is activated from a monomeric to trimeric form by oxidative, thermal and other stressors. Various studies show that HSF1 levels increase with cancer and decrease with aging and neurodegenerative disorders. It has a role in development as well as infections and inflammation. HSF1 is regulated by post-translational modifications and interactions with other proteins such as HSBP-1. Given its central importance in stress responsivity, various methods have been developed to identify HSF1 and its interacting partners. To date, multiple studies use conventional immunoprecipitation of HSF1 with commercially available antibodies which work well in cell lines but not whole tissue extracts. To remedy this shortfall, we developed a technique to retrieve activated HSF1 with an oligonucleotide link to a magnetic bead. The method captureheat shock protein genes.•This protocol allows isolation of trimeric forms of HSF1 from tissue lysate using magnetic beads conjugated with a short DNA sequence with specific binding to HSF1.•This method is easy, economic and does not require unique instrumentation.A method is proposed for generating application domain agnostic data for training and evaluating machine learning systems. The proposed method randomly generates an expert system network based upon user specified parameters. This expert system serves as a generic model of an unspecified phenomena. The expert system is run to determine the ideal output from a set of random inputs. These inputs and ideal output are used for training and testing a machine learning system. This allows a machine learning technology to be developed and tested without requiring compatible test data to be collected or before data collection as a proof-of-concept validation of system operations. It also allows systems to be tested without data error noise or with known levels of noise and with other perturbations, to facilitate analysis. It may also facilitate testing system security, adversarial attacks and conducting other types of research into machine learning systems. •Provides an application domain agnostic way to test machine learning technologies and facilitates the generalization of results.•Allows technologies to be tested with data with different characteristics without having to locate datasets that have these characteristics.•Utilizes randomly generated network to represent non-specific phenomena which can be used for training and testing machine learning techniques.Soil is one of the environmental compartments most affected by pollution. From this medium, the organic compounds can be emitted to the groundwater, the atmosphere, or the biota. Thus, having adequate methods of analysis of organic pollutants in this matrix is essential. However, the soil is a very complex matrix whose organic and inorganic components can determine the degree to which they are retained. Therefore, the methods must account for the various soil characteristics. In this study, the performance of an extraction method that had been already validated in clay loam soils for more than 300 organic compounds of very different nature including pesticides, PhACs, ARs, and POPs has been evaluated in four additional representative soil types of the agricultural land of the Canary archipelago sandy loam, sandy clay, clay and loamy sand. For this purpose, recovery experiments have been performed at a single concentration (50 ng g-1) in each soil type. When there is a significant difference according to the criteria applied for a given compound, a factor has been calculated to correct the difference in performance in each soil type.•These results allowed to broaden the range of soils that can be analyzed with the proposed methodology.•In the worst case, which is the loamy sand soil, the original methodology allows the analysis of 180 organic contaminants with adequate recoveries. For analytes outside the acceptable range in this soil and the other soil type analyzed, correction factors are proposed.
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